Comparative transcriptomes reveal pro-survival and cytotoxic programs of mucosal-associated invariant T cells upon Bacillus Calmette–Guérin stimulation

Mucosal-associated invariant T (MAIT) cells are protective against tuberculous and non-tuberculous mycobacterial infections with poorly understood mechanisms. Despite an innate-like nature, MAIT cell responses remain heterogeneous in bacterial infections. To comprehensively characterize MAIT activation programs responding to different bacteria, we stimulated MAIT cells with E. coli to compare with Bacillus Calmette-Guérin (BCG), which remains the only licensed vaccine and a feasible tool for investigating anti-mycobacterial immunity in humans. Upon sequencing mRNA from the activated and inactivated CD8+ MAIT cells, results demonstrated the altered MAIT cell gene profiles by each bacterium with upregulated expression of activation markers, transcription factors, cytokines, and cytolytic mediators crucial in anti-mycobacterial responses. Compared with E. coli, BCG altered more MAIT cell genes to enhance cell survival and cytolysis. Flow cytometry analyses similarly displayed a more upregulated protein expression of B-cell lymphoma 2 and T-box transcription factor Eomesodermin in BCG compared to E.coli stimulations. Thus, the transcriptomic program and protein expression of MAIT cells together displayed enhanced pro-survival and cytotoxic programs in response to BCG stimulation, supporting BCG induces cell-mediated effector responses of MAIT cells to fight mycobacterial infections.

Bacterial incubation of K562.hMR1 cells. We incubated K562.hMR1 cells with Listeria monocytogenes (L. monocytogenes strain J0161, Bei resources), Escherichia coli (non-pathogenic E. coli strain BL21, New England BioLabs), Mycobacterium bovis-(M. bovis-) derived Bacille Calmette-Guerin (BCG) vaccine strain (Pasteur) (18), and avirulent Mycobacterium tuberculosis (M. tuberculosis, strain H37Ra defective in ESX-1 secretion (19), Colorado State University, Fort Collins, CO) (20). We grew mycobacterial strains BCG and H37Ra for 5 to 6 days using middlebrook 7H9 complete medium in an orbital shaker at 37 o C and a speed of 270 rpm. E.coli and L. monocytogenes were cultured overnight using Luria-Bertani broth in an orbital shaker at 37 o C and a speed of 100 rpm. We harvested bacteria at the log growth phase, washed with phosphate buffer saline (PBS), and measured their absorbance (optical density at wavelength 600 nanometres, OD600) according to the report (21). OD600 provides a semi-quantitative measurement of bacterial cell numbers for MAIT cell activation (21). K562.hMR1 cells were incubated with E.coli and Listeria at an estimated multiplicity of infection (MOI, for cell to bacteria ratio) of 1:10 and with BCG or H37Ra at MOI of 1:100, considering a much faster growing rate of E. coli than mycobacteria during the overnight incubation.

Isolation and activation of primary human MAIT cells.
We obtained blood samples of healthy donors with written informed consent at the Hoxworth Blood Center in the University of Cincinnati and processed the deidentified blood samples according to the approved protocols by the Institutional Review Board. We then isolated human peripheral blood mononuclear cells (PBMCs) using Ficoll-paque gradient (GE Healthcare), incubated them with anti-V7.2 antibody (3C10) conjugated with PE (Biolegend), and performed positive selection with anti-PE antibody-conjugated magnetic beads (MACS, Miltenyi Biotec) according to manufacturer's instructions. These anti-V7.2-enriched primary human MAIT cells were co-cultured with bacterial-incubated K562.hMR1 cells in a ratio of 4:1 for around 15 hours together with anti-CD28 (clone CD28.2) antibody at 2ug/ml for co-stimulation. Strong MAIT cell activation in this assay was measured with upregulated CD69 + CD26 ++ MAIT cells as we reported (9) using anti-CD3/CD28 activation as a positive control.
The dependence on MR1-mediated antigen presentation was controlled with the conditions of anti-MR1 antibody (clone 26.5) blockade (22,23) and negative control bacterium L. monocytogenes, which was previously shown to be unable to activate MAIT cells (9) due to lack of metabolic pathways to produce riboflavin metabolites (10,24).

RNA-seq of human MAIT cells.
Upon co-culture of bacterial-incubated K562.hMR1 and MAIT cells, MAIT cells from three donors were first gated on V7.2 + CD161 + CD4 -CD8 + as our targeted major MAIT cell subset in this study and further sorted based on CD69 + CD26 ++ and CD69 -CD26 +/into activated versus inactivated MAIT cells (Fig. S1). Around one thousand cells were collected for each subset and lysed in the Lysis Buffer for total RNA extraction using mirVana kit (ThermoFisher, Grand Island, NY). Agilent Bioanalyzer and RNA 6000 Pico chip (Agilent, Santa Clara, CA) measured RNA integrity and showed a high quality of samples. NEBNext Analyses of differentially expressed genes (DEGs). Similar to our previous report (22), transcriptomic data were analyzed to identify DEGs, which were further used for pathway analyses. To identify DEGs, we aligned the sequence reads to the genome and converted them to intensity counts. EdgeR program on the Bioconductor R platform was used to compare resulted intensity counts to identify DEGs using a robust algorithm in R package, glmFit，a genewise negative binomial generalized linear model, to minimize raw data alteration and allow the comparison of multi-factorial comparisons among multiple conditions (25). We generated DEGs based on intensity fold changes (>2 folds) at a p-value of <0.05 between activated and inactivated CD8 + MAIT cells in each bacterial stimulation measured by the surface markers of CD69 + CD26 ++ and CD69 -CD26 +/-. We also compare genes with more than 2 folds of intensity changes between BCG and E.
coli stimulations with CD69 + CD26 ++ CD8 + MAIT cells based on a p-value of <0.1 to allow the variation from different batches of cell culture, bacterial stimulation, cell sorting, and gene sequencing. DEGs were shown with volcano plots generated with edgeR and ggplot2 programs on the R platform. Upregulated and downregulated genes between different stimulation conditions were compared using Venn diagrams. To predict shared functional clusters and pathways of DEGs, we applied ToppCluster program based on hypergeometric tests for functional enrichment (https://toppcluster.cchmc.org/) (26)  MAIT cells were gated on V7.2 + CD161 + CD4 -CD8 + as V7.2 + CD161 + gating has been used in multiple studies to detect MAIT cells (13,(29)(30)(31)(32), especially the bacterial-activated MAIT cells (13,33,34)